The Improved-Articial Fish Swarm Algorithm And Its Application In Coverage Optimization Of The Wireless Sensor Network

The artificial fish swarm algorithm(AFSA) has the advantages of strongrobustness, easy to implement,no special requirements for objective function and theinitial value of parameters.It has been widely used in intelligent control, parameteroptimization and many other fields. At present, the improvement of AFSA mainlyfocus on the improvement of the artificial fish’s behavior, adjustment of the algorithmparameters and integration with other intelligent optimization algorithms.Improvement of artificial fish swarm algorithm and its application to practicaloptimization problems have become a hot topic.Firstly,according to the low optimization accuracy of AFSA during the late periodof the algrithm, the artificial fish swarm algorithm which keep optimal strategy(KOAFSA) is proposed in this paper. Artificial fish swarm algorithm is used to searchfor the optimal value in the solution space, the optimal value is compared with thebulletin board each iteration. If the optimal value is superior to the bulletin board so itis assigned to the bulletin board, and if the optimal value is inferior to the bulletinboard so keep the original value. After M iterations there is no significant change,used brute force algorithm continue to search for the optimal value in the solutionspace to improve the accuracy of algorithm optimization; Secondly,focus on TSPproblem, a modified artificial fish-swarm algorithm which is based on dynamicregulation of configuring parameters(DRAFSA)is presented. The main ideas of theimprovements are as follow: the parameters are adjusted dynamically to improveconvergence speed. removing crossover operator and further optimizing operator areintroduced to improve the search precision; Finally,coverage optimization of thewireless sensor networks is to guarantee the quality of network service. A fitnessfunction is established by weighting the node utilization and coverage,at last appliedthe further optimizing-artificial fish swarm algorithm to solve coverage optimizationproblem of the wireless sensor networks.In order to verify the validity of the algorithms,for the artificial fish swarmalgorithm which keep optimal strategy, the results of function test show that thealgorithm has excellent convergence; TSP is used to test artificial fish-swarmalgorithm which is based on dynamic regulation of configuring parameters,thesimulation results show that the algorithm improved convergence speed and optimization accuracy; applied the artificial fish swarm algorithm which keep optimalto coverage optimization of wireless sensor network, the experimental results showthat the algorithm received a better effect of network coverage.